Submission¶

Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace

In [2]:
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px

init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
In [3]:
#load data
df = px.data.gapminder()
df.head()
Out[3]:
country continent year lifeExp pop gdpPercap iso_alpha iso_num
0 Afghanistan Asia 1952 28.801 8425333 779.445314 AFG 4
1 Afghanistan Asia 1957 30.332 9240934 820.853030 AFG 4
2 Afghanistan Asia 1962 31.997 10267083 853.100710 AFG 4
3 Afghanistan Asia 1967 34.020 11537966 836.197138 AFG 4
4 Afghanistan Asia 1972 36.088 13079460 739.981106 AFG 4

Question 1:¶

Recreate the barplot below that shows the population of different continents for the year 2007.

Hints:

  • Extract the 2007 year data from the dataframe. You have to process the data accordingly
  • use plotly bar
  • Add different colors for different continents
  • Sort the order of the continent for the visualisation. Use axis layout setting
  • Add text to each bar that represents the population
In [4]:
# YOUR CODE HERE
df_2007 = df.query('year==2007')
dfgroup = df_2007.groupby(df.continent).pop.sum()
fig = px.bar(dfgroup, x="pop", y=dfgroup.index, orientation='h', color=dfgroup.index)
fig.update_yaxes(title='continue')
fig.show()

Question 2:¶

Sort the order of the continent for the visualisation

Hint: Use axis layout setting

In [5]:
# YOUR CODE HERE
df_2007 = df.query('year==2007')
dfgroup = df_2007.groupby(df.continent).pop.sum()
fig = px.bar(dfgroup, x="pop", y=dfgroup.index, orientation='h',color=dfgroup.index)
fig.update_yaxes(title='continue')
fig.update_yaxes(categoryorder='total ascending')
fig.show()

Question 3:¶

Add text to each bar that represents the population

In [6]:
# YOUR CODE HERE
df_2007 = df.query('year==2007')
dfgroup = df_2007.groupby(df.continent).pop.sum()
fig = px.bar(dfgroup, x="pop", y=dfgroup.index, orientation='h',text='pop',color=dfgroup.index)
fig.update_yaxes(title='continue')
fig.update_traces(textposition="outside",texttemplate='%{text:,.2s}')
fig.update_yaxes(categoryorder='total ascending')
fig.show()

Question 4:¶

Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years

In [7]:
# YOUR CODE HERE
dfgroup = df.groupby(['continent','year']).sum()
dfgroup.reset_index(inplace=True)
fig = px.bar(dfgroup, x="pop", y='continent', orientation='h',color='continent', animation_frame='year',animation_group='continent',range_x=[0,4000000000])
fig.update_yaxes(title='continue')
fig.update_yaxes(categoryorder='total ascending')
fig.show()

Question 5:¶

Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years

In [8]:
# YOUR CODE HERE
fig = px.bar(df, x="pop", y='country', orientation='h',color='country', animation_frame='year',animation_group='country',range_x=[0,1500000000])
fig.update_yaxes(title='country')
fig.update_yaxes(categoryorder='total ascending')
fig.show()

Question 6:¶

Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation

In [9]:
# YOUR CODE HERE
fig = px.bar(df, x="pop", y='country', orientation='h',color='country', animation_frame='year',animation_group='country',height=1000,range_x=[0,1500000000])
fig.update_yaxes(title='country')
fig.update_yaxes(categoryorder='total ascending')
fig.show()

Question 7:¶

Show only the top 10 countries in the animation

Hint: Use the axis limit to set this.

In [10]:
# YOUR CODE HERE
fig = px.bar(df, x="pop", y='country', orientation='h',color='country', animation_frame='year',animation_group='country',range_x=[0,1500000000])
fig.update_yaxes(title='country')
fig.update_yaxes(categoryorder='total ascending')
fig.update_layout(yaxis_range = [132.5,141.5])
fig.show()
In [ ]: